Title:
Nonlinear Analysis of Cyclically Loaded Reinforced Concrete Structures
Author(s):
M. Elmorsi, M. Reza Kianoush, and W. K. Tso
Publication:
Structural Journal
Volume:
95
Issue:
6
Appears on pages(s):
725-739
Keywords:
cyclic loads; finite element; hysteresis; reinforced concrete; steel reinforcement; structural wall
DOI:
10.14359/586
Date:
11/1/1998
Abstract:
This paper presents a simple and reliable constitutive model for predicting the response of reinforced concrete under cyclic loading. The proposed model is based on the findings of previous experimental and analytical studies. The model adopts the concept of a smeared crack approach with orthogonal cracks and assumes a plane stress condition. It is comprised of two independent functions: the normal stress function and the shear stress function. The normal stress function defines the stress-strain behavior of concrete under cyclic tension and compression. The important aspects of concrete behavior included in the normal stress function are tension stiffening; crack opening and closing; compression hardening and softening; degradation of concrete strength and stiffness in the direction parallel to the crack; and compression unloading and reloading. The shear stress function defines the cyclic relationship between the shear stress and the shear strain of concrete. A smeared reinforcing steel model is included to describe the cyclic stress-strain behavior of the steel reinforcement. The aspects included in the steel model are yielding, strain hardening, the Bauschinger effect, and the cyclic unloading and reloading rules. Most of the previous analytical models under cyclic loading have shown great success at the element level but, due to their complexity, they have not been used in analyzing actual reinforced concrete (RC) structures. The proposed model is simple enough to be incorporated into any nonlinear finite element analysis program used in analyzing full structures. The accuracy of the proposed model is in agreement with available analytical and experimental data.